Method and system for image processing

ABSTRACT

A method for image processing in a computerized system reduces the amount of memory required for image processing and produces a layered effect which permits complex manipulation such as scaling and rotation without long delay, while allowing earlier versions of the visual image to be recalled. The method involves pre-processing, image editing and raster image processing.

BACKGROUND OF THE INVENTION

[0001] This invention relates to computer processing in general, andmore particularly to a method and system for image processing. Thepatent application claims priority of French patent application No.93.03455, filed Mar. 25, 1993, the contents of which are hereinincorporated by reference.

[0002] The present invention was created in response to the shortcomingsof the current generation of image retouching systems. Other retouchingsystems use one of two methods for handling images: (1) highresolution/low resolution (high, res/low res), and (2) virtual image.Each of these two approaches overcomes some major obstacles, howeverneither fully responds to the needs of today's color professionals forhigh quality, and fast response at an affordable price.

[0003] In the high res/low res approach, the complete scanned image(referred to as the “high res” image) is subsampled to yield a muchsmaller image (referred to as the “low res” image). Because previousimage retouching systems did not yield “real time” performance whenhandling large images (over 10M or 10 million bytes), it was necessaryto invent an approach to allow the retouching system work on a smaller,i.e. low res image that would yield acceptable response times for theoperator. Using this approach, retouching actions are stored in ascript. When retouching is complete, the script is typically passed to amore powerful, and expensive, server and “executed.” That is, theactions contained in the script are applied to the high res image, whichresults in a high quality final image. The disadvantage of this approachis that the operator does not work with the actual image or at highlydetailed levels (particularly for a magnified “close-up” of a portion).As a result, it is not always possible to perform highly detailedretouching actions such as silhouetting and masking. Moreover,unpleasant surprises may occur upon execution.

[0004] The virtual image approach, commonly used by desktop imageediting packages (e.g. MacIntosh or Windows types), manipulates a copyof the actual image held in memory. In some cases, one or more copies orintermediate drafts are held, enabling the user to revert to a previouscopy if an error is introduced. Using the virtual image approach, theimage itself is transformed as retouching effects are applied.

[0005] The virtual image approach suffers two important shortcomings:first, large amounts of memory are required; and second, each effect isapplied immediately to the entire image so that complex manipulation,such as large airbrushing, scaling and rotation, incur long processingdelays.

[0006] Prior image retouching systems have used large mainframecomputers or work stations and proprietary hardware. For example, U.S.Pat. No. 5,142,616, issued Aug. 25, 1992 to Kellas, et al., teaches anelectronic graphic system. In this system, data relating to auser-defined low resolution image functions to control an image by thecombining other image data with data defining a low resolutionrepresentation of the initial image. Once desired modifications havebeen achieved, the image is displayed on a display monitor so that a lowresolution control image is converted to a high resolutionrepresentation. Stapleton, et al., U.S. Pat. No. 4,775,858, issued Oct.4, 1988, also teaches the use of a large frame store to produce an imageof higher resolution than that found on a television screen.

[0007] Due to the high amount of memory required for processing,personal computers have proven very slow and marginally acceptable.Moreover, even with larger mainframe systems, there is not always a goodcorrelation between the monitor and the printed image since there is notalways a way to visualize the final image on the display device. Thus,discrepancies can be introduced due to differences between screenresolution and print resolution. Other relevant patents include: U.S.Pat. No. 5,179,651 issued Jan. 12, 1993 to Taaffe, et al., U.S. PatentNo. 5,065,346, issued Nov. 12, 1991 to Kawai, et al., U.S. Pat. No.4,656,467, issued Apr. 7, 1987 to Strolle, U.S. Pat. No. 4,833,625,issued May 23, 1989 to Fisher, et al., U.S. Pat. No. 4,288,821, issuedSep. 8, 1991 to Lavallee, et al., and U.S. Pat. No. 4,546,385, issuedOct. 8, 1985 to Anastassiou.

[0008] Numerous image processing procedures currently exist. Common toall procedures is modification of an image through recalculationoperations to irreversibly rearrange dots or picture elements (“pixels”)of an original image (or those resulting from the most recentmodification) into a new arrangement.

[0009] Perhaps the greatest disadvantage of known procedures stems fromthe image that is displayed on the monitor not being identical to theimage that will eventually be printed, rendering the operator unable tosee the work as it will actually appear in print. Anomalies anddiscrepancies can therefore occur in the printed image. Known procedurescannot resolve the fact that the image displayed on the operator'smonitor screen is in most cases vastly less defined than the scannedimage held in the computer's memory. (This is untrue only in the case ofsmall, low resolution images.) Resolution (as measured in dots per inch)of modern display monitors is far less than the resolution of printedcolor images.

[0010] A second and perhaps equally important disadvantage of knownimage processing techniques is that the image editing effects areapplied sequentially, i.e. step-by-step. This incurs a severedegradation in the quality of the original image if many image editingeffects are applied to the same portion of an image.

[0011] Operations carried out on an image usually require a high degreeof processing power. If processing power is unavailable, then the timerequired to carry out the operation becomes unacceptably long, thusreducing the scope and sophistication of possible operations to becarried out on the image. For example, airbrush strokes are currentlyextremely limited in size as a result of the extreme processing powerneeded to calculated image changes.

[0012] The irreversible nature of image processing using knownprocedures precludes the operator from easily implementing any secondthoughts. Presently, the only way to correct an airbrush stroke whichdoes not achieve a desired effect is to superimpose a new stroke(instead of merely erasing the unsuccessful stroke). Alternatively,computers equipped with large memory can save intermediate steps.However, this requires a huge amount of memory (e.g., a single 8½″×11″×300 dots per inch (dpi) figure requires over 33 million bytes).

[0013] The present invention overcomes these shortcomings and permitsrapid and powerful editing functions even on less powerful desktopcomputers, by employing at least one, more preferably two and mostpreferably three new and independent processes: preprocessing, imageediting, and raster image processing.

[0014] The subject invention advantageously uses what I call aFunctional Interpolating Transfer System (FITS) to greatly speed editingof an image on standard microcomputers, thus eliminating the need forexpensive workstations or special hardware. FITS breaks down imageprocessing into three steps: preprocessing, image editing and FITSraster image processing. This results in a virtually instantaneousresponse and eliminates waiting for file saving or processing updates.With this technique, limits on file size and resolution disappear.

[0015] Preprocessing in the invention (brand name “FITS”) involvescreating a specially formatted version of an image which allows imageediting to progress at rapid speed.

[0016] Image editing refers to the process of retouching, combining orotherwise modifying images, to create the final desired image. Imageediting involves, in the broadest sense, all processing operationsperformed on an original image. This includes the combining of images,effects such as sharpening, blurring, brightening, darkening,distortion, and include modifications to the color or appearance of allor part of a original image.

[0017] Color changes may be achieved in a variety of ways includingglobal changes to the chromatic range of the image, or selective changeto individual colors, e.g. changing blue to red.

[0018] Raster image processing (“RIP”) is performed in two instances:(1) each time a new screen view is generated for display on a monitor,and (2) when an output page is generated for the purpose of printing orincorporated into another system such as a desktop publishing system.FITS raster image processing combines the input images with themodifications generated in the second stage (image editing) to createeither a screen or print image. The output image generated by the FITSRIP can have any resolution; thus it is said to be resolutionindependent.

[0019] FITS raster image processing (“FITS RIP”) involves taking theensemble of image manipulations (the various steps or “layers” ofchanges) that are performed during the image editing process andcomputing a single image for purposes of printing or display on amonitor. Modifications to the image, made during image editing, arecharacterized in a manner that is independent of the resolution of theinput images or final output image. During a FITS RIP, layers are firstcombined mathematically for each pixel or selected pixels in the desiredimage, rather than by applying each layer successively to the originalimages. For each final pixel, a single mathematical function isgenerated that describes the color, in an arbitrary color space, at thatpoint. If, as preferred, only a sample of pixels are fully computed foreach layer of change, the color values of intermediate pixels arecomputed by averaging the mathematical functions of the neighboringpixels and applying that function average to the original pixel's color,rather than simply averaging the color values of the surrounding pixels.This approach results in a time savings in overall image handling and ahigher quality resulting image.

[0020] In the FITS approach, the image editing actions are characterizedby parameters to mathematical functions and these are storedlayer-by-layer in a file separate from the original image(s). Eachintermediate modification to the image is effectively saved in a layerand each layer can be independently modified, deleted or reordered. Theparameters can be stored for points in a grid that is itself independentof the “dots-per-inch” resolution (dpi) of either the original importedimages, or the final output images. As a result, images for display orprint can be generated at an arbitrary resolution.

[0021] Substantially less memory is required during image editing thanwith the virtual image approach since only the changes to each layer arestored, not entire image each time. As a result, a sophisticated,heavily retouched new image consisting of over 10 layers can bedescribed in a FITS file of 2-5 megabytes (2-5M), as compared with over30M (megabytes) for existing virtual image systems to store a 1 page newimage (at 300 dpi resolution). Thus, the FITS approach yields a 10 to 1average savings per page of image, and substantially more for largerimages or higher resolutions. Note that 600 dpi images are now quitecommon for high quality publishing, and this is likely to increase inthe future.

[0022] To sum up, current computerized image processing for obtaining ahigh definition image suffers from the dual disadvantages of requiringextremely high processing power, a limitation of productivity andcreativity for the operator due to the irreversibility of image editingsteps, and the quality restrictions inherent in a pixel-based approach.

[0023] The subject invention, on the other hand, provides a computerizedimage processing procedure which enables the operator to rapidly carryout advanced graphic operations, and to reverse decisions asrequired—without in any way affecting the definition or precision of thefinal image.

SUMMARY OF THE INVENTION

[0024] The invention provides an image processing system for thecreating and editing images that are resolution independent andcharacterized by a series of layers, or image objects, that can becombined together to yield an output image, at any resolution, fordisplay or print. The new method of image processing in a computerizedsystem creates a high performance image representation, that yields muchfaster image processing by supplying data defining an original imageinto the system and reorganizing the original image data.

[0025] One aspect of this method (pre-processing, which I call “IVUE”format) comprises the following steps: (1) supplying data defining theoriginal image into the system, (2) assigning pixels from the originalimage to pixels in the new image format in such a way that the new imageis organized in groups (preferably rectangles and most preferablysquares), each of which can be individually compressed (using JPEG oranother compression algorithm) to yield reduced image size and fasteraccess over a network, (3) creating a second, lower resolution, image byaveraging groups of pixels falling within a first predetermined area (orneighborhood) into an averaged pixel, and performing this computationacross the entire original image; this second image is also organized ingroups, e.g. squares, (4) repeating the previous step, and therebycreating. succession of decreasing resolution images, which are storedadjacent to the first two, until a number of pixels less than or equalto a preselected number of pixels remain, and (5) saving the resultingimage representation on a storage device.

[0026] Also provided is a method for image processing in a computerizedsystem that involves applying changes to one or more original images asa series of “layers” in which the changes are recorded asresolution-independent mathematical functions. This approach has theproperty that only the final result of the retouching effects in a layerneeds to be calculated or characterized and the effects are wholly orpartially reversible. The layers themselves are independent and may atany time be modified, deleted, or reordered. The changes in each layerare generally characterized in a way that is independent of resolution.

[0027] This aspect of the method comprises the following steps: (1) fora layer 1, 2, 3, etc., generally number “i”, displaying the results ofthe image processing up to and including all effects applied andoriginal effects inserted for the “i−1”th layer (e.g. 5th layer) (2)recording all effects applied in the ith layer (e.g. 6th layer) asparameters to mathematical functions that define the effect, so that foreach pixel in the displayed image that is modified there is a singlefunction that describes the resulting modification, (3) when theoperator terminates processing of the ith layer these parameters aresaved along with the parameters that describe changes to the precedingi−1 layers.

[0028] Also provided is a method for image processing in a computerizedsystem that enables a raster image to be computed, either with theability of displaying the image on a computer monitor or for printingthe image.

[0029] This method involves: (1) sampling an original image to beprocessed with a definition grid so as to retain a predetermined numberof dots from all of the dots contained within the original image, thepredetermined number being equal to or less than the number required toeither display the result on a computer monitor or to generate an outputfile destined to be printed; and (2) for each dot in the grid togenerate a single mathematical function that represents the cumulativeeffect of all the layers in the image at that point. This is done byprocessing the resulting image into elementary recurrent operations eachbroken down into three parts and providing, based on the result of theprevious elementary operation, these three parts added to each other,(3) filling in sufficient additional dots, or pixels, within the grid toreach the required resolution for screen or print by interpolating thefunctions at the surrounding gridpoints to obtain a single function thatcan be applied to intermediate pixels and will yield an interpolatedcolor value for that pixel, (4) computing the color value results foreach pixel, and (5) either printing or displaying the result, or storingthe result on a computer storage device.

[0030] The invention may use a method of image processing in acomputerized system, comprising: (a) supplying data defining an originalimage into the system, (b) assigning pixels from the original image topixels in a new first image format so that the first image is organizedinto groups of pixels, each of the groups being individuallycompressible to yield a reduced size image, and (c) reducing the numberof assigned pixels to form a reduced resolution image by averaging(preferably using a Gaussian function to weight the average for pixelproximity) a particular number of adjacent pixels falling within a first(preferably predetermined) area into a first averaged pixel, organizedby the groups of pixels, and performing this computation across theentire first image format, to form a reduced definition image.

[0031] This method may (and preferably does) further comprise reducingthe number of the first averaged pixels by averaging groups of pixelsfalling within a second predetermined area into a second averaged pixel,organized by the groups of pixels, performing this computation acrossthe entire second image format, and (preferably) repeating this stepuntil a preselected or lower number of pixels remain, the remainingpixels forming a reduced definition image. Data defining the reduceddefinition image may be modified by a user to obtain a desired resultand the system or user may save a copy of the data or mathematicalfunctions defining the pixels that form the desired result. Moreover,the data defining the original image may be added to the data definingthe pixels forming the desired result, and forming an image from theadded data.

[0032] The invention may also include a method of raster imageprocessing which includes: (a) adding data defining an original image todata defining modifications to a reduced definition image, and (b)forming an image from the added data. Preferably, this is accomplishedby a computerized system which comprises: (a) means for adding datadefining pixels forming an original image to data defining modificationsto a reduced definition image, and (b) means for forming an image fromthe added data.

[0033] The invention may also include a computerized system for imageprocessing, comprises: (a) means for assigning pixels from an originalimage to pixels in a new first image format so that the first image isorganized into compressible groups of pixels, and (b) means for reducingthe number of assigned pixels to form a reduced resolution image byaveraging a particular number of adjacent pixels falling within a first(preferably predetermined) area into a first averaged pixel, organizedacross the entire first image format, to form a reduced definitionimage. Preferably, means are provided for reducing the number of thefirst averaged pixels by averaging groups of pixels falling within asecond predetermined area into a second averaged pixel, organized by thegroups of pixels, performing this computation across the entire imageformat, and repeating this step until a preselected number of pixelsremain, the remaining pixels forming a final reduced definition image.

BRIEF DESCRIPTION OF THE FIGURES

[0034]FIG. 1—A schematic representation of processing steps of theinvention.

[0035]FIG. 2—A schematic representation of interconnections betweensystem hardware.

[0036]FIG. 3—A schematic representation of software architecture.

[0037]FIG. 4A—A numerical/graphic illustration of a pixel reductiongrid.

[0038]FIG. 4B—A schematic illustration of a pixel reduction grid.

[0039]FIG. 5—A schematic illustration of the IVUE format.

[0040]FIG. 6—A schematic illustration of the FITS reduction.

[0041]FIG. 7—A schematic illustration of 2 i×2 j density functions.

[0042] FIGS. 8A-F—Depictions of computer monitors showing the inventionin use.

DETAILED DESCRIPTION OF THE INVENTION

[0043] To aid in understanding the invention, the following overview isprovided:

[0044] The subject invention was created in response to the shortcomingsof the current generation of image retouching systems. The currentcommon personal computer approach, often referred to as virtual image,manipulates a copy of the actual image, which is held in memory.

[0045] Functional interpolating transformation system (FITS) takes aradically different approach in which the underlying image is preserved,and changes are recorded in separate layers in a file, named FITS. Byprocessing only changes to the current screen, FITS computes only whatis needed, when needed. Further, all modifications are resolutionindependent and can be used to generate output images at any level ofresolution (commonly measured in dots per inch or dpi). FIG. 1 shows anoverview of the FITS model, FIG. 2 depicts the interaction of hardwareinvolved, and FIGS. 8A-F show the system in use.

[0046] When image editing is complete, the operator initiates acomputation which applies the changes across the entire image. Thisfinal processing is termed FITS raster image processing (RIP) and isvaguely analogous to Postscript raster image processing (a system forgenerating the raster image that corresponds to pages of printedinformation described using the Postscript language).

[0047] Unlike many high-end and mid-range color systems that oblige theoperator to work with a low-resolution image, FITS operates inhigh-resolution, i.e., the operator may at any time access anyinformation contained in the original image(s) without being limited bythe FITS processing approach.

[0048] The subject invention will now be described in terms of itspreferred embodiments. These embodiments are set forth to aidunderstanding the invention, but are not to be construed as limiting.Moreover, the invention includes using only some aspects, or indeed,only one aspect, of the most preferred method.

[0049] The new image processing system is for creating and editingimages that are resolution independent where the images arecharacterized by a series of layers that can be combined together toyield an output image, at any resolution, for display or print. Notethat the term “layers” can also refer to image objects that are managedindependently and combined in pixel format for purposes of output.

[0050] The general expression for characterizing an image, using thisapproach, is as follows:

[0051] f_(n)(x, y)=a combination of one or more of such components as:

[0052] external image(s)

[0053] position independent terms

[0054] position dependent terms

[0055] f_(n−1)(x, y) or prior layers

[0056] Where f_(n)(x, y) is the color value of a point of an image, inan arbitrary color space (e.g. RGB, or CMYK), at a layer n.

[0057] External image—may be any external image. In FITS, these imagesare preferably transformed into Input format for fast processing.Generally, however, the images may be in any format.

[0058] Position independent terms—these are modifications which do notdepend on the position of the image element. For example, a colorapplied in a layer to the entire image.

[0059] Position dependent terms—these are geometric transforms, colormodifications, etc. supplied selectively to different regions of theimage. f_(n−1)(x, y)—the function that describes the color in thepreceding layer.

[0060] The color value of a point (x, y) in layer n may be defined by asingle mathematical function which combines an external image or images,position dependent terms, position independent terms, and the functiondefining the point (x, y) for the preceding layer.

Three Steps

[0061] FITS comprises three independent processes: pre-processing, imageediting, and FITS raster image processing (FITS RIP). FITS is overviewedin FIGS. 1 and 6. FIG. 3 illustrates the software architecture.

[0062] Prepossessing. Initially the input image, in TIFF or anotherstandard format (such as Postscript), is reorganized to create aspecially formatted new file, termed IVUE. The IVUE file is used duringimage editing and also during the FITS RIP. It is reorganized in such away that a new screen full of image data may be quickly constructed. Thescreen's best resolution can be used, both for the full image and forclose-up details. As an option, a second IVUE file may be created thatis compressed using conventional methods, such as JPEG, or by othermethods The IVUE file contains all of the original image data.

[0063] The image is divided into squares. Each of the squares in each ofthe various image representations within the IVUE file may beindividually compressed (see FIG. 5). This is a unique approach sinceother image processing systems compress the entire image. The resultingfile, termed .IVUE/C, is considerably smaller than the original file.The actual size of the file depends on the compression level used togenerate the IVUE file. Average compression will yield an 8 to 1 averagereduction in the size of the image. In a first product to be based onthis invention, to be called Live Picture, for example, threecompression levels may be selected when creating the IVUE file.

[0064] Saving the IVUE sampled files together with the original filetakes up only about 30% more space than the original alone. For example,for ¼ sampling with the original being assigned 1, the memory requiredis$1 + \frac{1}{4} + \frac{1}{16} + \frac{1}{64} + {\frac{1}{256}\quad \cdots}$

[0065] or approximately 1.3 times the original file size.

[0066]FIG. 4A shows a 10×10 pixel box in which each of the pixels areidentified by a column, row number. The smaller enclosed box is a 4×4matrix which is reduced to a single point. One way to complete thereduction, or apply the FITS layer to do the RIP, is to select an originpoint (in this case, 1,1, is selected). Two points are then selectedoutside of the box along the column and row, as depicted, point 1,5 and5,1. By knowing these three pixels, each of the pixels in the box can beidentified by a simple division by two. For example, pixel 1,3 can bedetermined by averaging 1,1 and 1,5. By thinking of column 1,1-1,5 as avector and row 1,1-5,1 as another vector, each of the pixels can beidentified and reconstructed. Another advantage to this system ofpicking two points outside of the 4×4 pixel square is that a redundancyexists. Returning to FIG. 4A, pixel 1,5 acts as the origin for the 4×4box above the initial box described. Again, the 5,1 pixels serves as theorigin for the next 4×4 pixel box. Turning now to the larger black linesquare, (having corner points 1,1, 1,8, 8,8, and 8,1, this 16×16 squarewill after the first set of reductions, be a 4 pixel square which can behandled in much the manner described above. Once the 256 pixel squareremains, or some other predetermined sized square or area, the next stepof image editing can occur. Alternatively, the IVUE sampling to make alower resolution image can average 4 pixels to make 1, or sample a largegroup using weighting (e.g. Gaussian) to achieve any desired ratio orcompression.

[0067] A compressed image can be stored either on the operator'sworkstation or on a network file server. This approach greatly reducesthe disk requirement. In addition, when the IVUE/C file is held on afile server, network delay in accessing the image is minimized sinceFITS accesses the IVUE file one screen at a time.

[0068] There are two principal advantages of using this compression: (1)only the IVUE file is used during image editing; thus, use of acompressed file decreases the disk requirement on the retouchingstation, and (2) during image editing, FITS accesses the IVUE file onescreen at a time; thus if the image is on a network image server use ofthe compression option will greatly reduce operator wait times inducedby network delay.

[0069] The JPEG (or the like) compressed image is used only during thescreen editing step, where the quality of the compressed image isperfectly acceptable. However, the full image, also in IVUE format, isused during the FITS RIP, in order to obtain the highest quality image.So while JPEG may be used to improve a speed and memory, it does notlessen the quality of image. This last point is key because many peopleincorrectly assume that the use of JPEG will degrade image quality.

[0070] Preprocessing to IVUE format is fast; for example an A4 imagetakes approximately 1 ½ minutes on a Mac Quadra. Generally, a TIFF imageis reprocessed at the rate of ½ megabyte per second.

[0071] The following method may be used to generate an IVUE image, whichcomprises a succession of reduced resolution images each of which isstored as a rectangle.

[0072] 1) The original image, in a standard or proprietary image formatis opened (i.e., accessed on a storage device).

[0073] 2) The original image is used to create the first, fullresolution image in the IVUE file. It is preferably stored as asuccession of p pixel×q pixel rectangles. Each rectangle then containsp×q pixels, that is each rectangle can be considered as a series of prows, each containing q pixels. The rectangles are stored sequentiallyon disk and for each square (to simplify further) the rows are storedsequential (row 1, row 2, row 3, . . . row p). (See FIGS. 4A, 4B and 5for organization of rectangles). Each rectangle may be encoded usingJPEG or another compression scheme.

[0074] 3) A subsequent, reduced resolution image is created from theprevious image, if there are more than p×q pixels in the previous image.Essentially, a neighborhood of pixels in the original image are averagedto provide a single pixel in the second image. The image is reduced ineach dimension, x and y, by a factor of 2 (or whatever is selected)yielding a 4 to 1 reduction in size for the subimage.

[0075] The general computation for computing f_(n+1)(i, j), the pixel atpoint i, j in the n+1st subimage is:

f _(n+1)(i,j)=∫

(x,y)·f _(n)(x,y)dxdy

[0076] in which:

[0077]

(x, y) is an arbitrary probability density function integrating over theentire space of real numbers, i.e. a weighting function, that takes intoaccount the contribution of the neighboring area. Thus we may consider

(x, y)εν(2 i, 2 j) or a selection of elements in the vicinity.

[0078] ε is an element of.

[0079] ν is a neighborhood of, and thus ν(i, j) is the neighboring areaof the point i, j.

[0080] As a density function,

(x, y) satisfies the following:

1=

(x,y)dxdy

0<

(x,y)<1 for all (x,y)

[0081] The presently preferred weighting function is a Gaussian densityfunction. However, other functions may be used as well.

[0082] As an example, the neighboring weighted average has beenimplemented on a computer as depicted in FIG. 7. In this case:

f _(n+1)(i,j)=½(f _(n)(2i,−1,2j))+⅛(f_(n)(2i+1,2j))+⅛(f _(n)(2i,+1,2j))+⅛(f_(n)(2i,2j−1))+⅛(f_(n)(2i,2j+1))

[0083] Alternatively, an equation which may be used for computingf_(n+1)(i, j), the pixel at point i, j in the n+1st subimage is:

f _(n+1)(i,j)=∫

_(2i2j)(x,y)·f _(n)(x,y)dxdy

[0084] where

[0085]

_(ij)(x, y) is the probability density function for pixel (i, j) atpoint (x, y). Usually, (x, y) is near to the origin point (i, j), thatis in the “neighborhood.” Thus E is the weight (such as 50% for nearpoints, 20% for more distant points) of any particular neighbor point x,y relative to the “home base” or origin of i, j. The weights are set upto total 100%, and so that E is positive (not zero) in the definedradius of the neighborhood (which can but need not include the wholeimage). Once E goes to zero, there goes the neighborhood, that is,points at or beyond that distance are not weighted in. Thus

[0086] 1 = ∫E_(ij)(x, y)xy

[0087] for all (i, j) and

0<

_(ij)(x,y)<1

[0088] for all (x, y)

[0089] This new, reduced image may be stored in rectangles of p×q pixelsas well.

[0090] 4) The third step may be repeated, creating a sucession ofimages, each (say) ¼ the size of the last, until a subimage of less thanp×q pixels is created. This is the last subimage. If this last subimagecontains less than p×q pixels, the remaining pixels may be filled fromthe neighboring squares or may be set to 0.

[0091] 5) The entire image format is saved on a storage device.

[0092] Image editing. Image editing refers to the process of retouching,creation and composition of images. The operator successively applieseffects such as blur, smooth, and transformations such as rotation andscaling. Additional images can be inserted at any time and, if desired,with transparency and masking.

[0093] Each editing action is represented by a mathematical function andrecorded in a file named .FITS. The .FITS file can be considered as adatabase of commands or layers, and is a very compact representation.

[0094] FITS implements types of layers, referred to as FITS modes. Foreach mode a set of actions are available and can be freely applied. InLive Picture, the operator will be able opt to initiate a new layer atany time, and when a new mode is selected, a new layer is automaticallycreated and all subsequent actions are contained within this new layer(until a new layer is created).

[0095] FITS modes include: image insertion (insertion of a scannedimage), painting, pattern, filters, lighting effects, mirror, lineworkand plug-in (i.e. a layer defined by an arbitrary application). Text istreated as a special case of linework, since it can be composed ofBezier curves. In fact, there are two types of image insertion modes:standard and advanced. The advanced mode offers the opportunity todistort the image at the price of additional processing and a slightdecrease in response time.

[0096] With FITS, each image editing action is represented by amathematical function. When the operator finishes working on a layer,the parameters of these functions are recorded in a file named FITS.Only the resulting aggregate modifications to the underlying image arerecorded. If, for example, the operator applies an effect and thenerases it then nothing is stored. Or, an artist may use hundreds ofbrush strokes to create a complex painting, yet the FITS representationdescribes the resulting painting and not the sequence of brush strokesused to create it.

[0097] Thus, FITS typically only records the final effect and notnecessarily each image editing action. This saves processing time andalso results in a very compact representation of the image editingsession within a FITS file. For example, if an A4 image, stored in a 35Mbyte file is heavily retouched, in (ten or more layers), the .FITS filewill only grow about 2-5 MB.

[0098] The FITS retouching file may be saved at any time, and may laterbe reused or modified. At any time, either during the image editingsession, each layer can be accessed and re-edited.

[0099] FITS Raster Image Processing (FITS RIP).

[0100] The invention provides a computerized procedure for creating araster image. This procedure is used both to create a new view of theimage on a computer monitor and to create a high resolution outputimage. The procedure preferably has the following characteristics:

[0101] Based on the area of the image to be raster image processed(RIP'ed), which is generally determined by the operator, a definitiongrid is constructed in such a way as to retain, from all the pixels tobe processed, points equal at the most to the number that can bedisplayed on the monitor screen, For fast processing, a ratio of 1 dotto 16 pixels can be used. The area to be RIP'ed refers to a portion orall of the image to be displayed or processed for printing. Theobjective is to compute the color value resulting from the superpositionof a series of layers. The color value is in an arbitrary color space.Commonly, this is in either the colorspace named RGB, defined by thethree primaries red, green, blue, or in CMYK, defined by the threecolors cyan, magenta, yellow and an additional value for black.

[0102] For one point in each definition grid, the general expression forthe color value of that point is computed. In practice, a simplifiedform of the general expression is generally used that can describe mostimage editing actions. This form is termed “elementary operation” and ithas the advantage of being relative simple to compute.

[0103] The elementary operations are broken down in turn into threestages and when combined a new result (layer i), based on the result ofthe previous elementary operation (layer i−1). The three stages are:

[0104] first, the adoption in the new layer (i) of a color dot (x, y)from the previous layer (i−1) with a weighing (α_(i)) ranging from −100%to 100% (i.e., margins from +1 to −1 and including positive and negativevalue),

[0105] second, the importing of an external image (I_(i)) into the layeri, that is, the importing of a color dot from the image (ii), afterchromatic and geometric transformation (P_(i)(x, y)) of this dot to addit to the color dot (x, y) of the layer (i), the degree of replacementof the dot of the layer (i) by the dot imported from the image (I_(i))being defined by a scalar β(x, y) with values from −100% to 100%.

[0106] third, an additional color term γi(x, y) applied to the dot (x,y) of the layer (i). This term may take into account painting or otherchromatic effects.

[0107] each elementary operation (i) being defined by the equationtaking account of the previous layer or operation (i−1):

[0108] in which:

φ_(i)(x,y)=α_(i)(x,y)·φ_(i−1)(x,y)+β_(i)(x,y) I _(i) [P_(i)(x,y)]+γ_(i)(x,y)

[0109] or alternatively:

[0110] where

φ_(i)(x,y)=α_(i)(x,y)·φ_(i−1)(x,y)+I _(i) [P _(i)(x,y)]+γ_(i)(x,y)

[0111] α_(i)(x, y) is a scalar function of the dot (x, y) correspondingto the presence at this dot of the image resulting from the previouselementary operation φ_(i−1)(x, y),

[0112] φ_(i−1)(x, y) is a function representing the previous elementaryoperation,

[0113] β_(i)(x, y) is scalar function corresponding to the presence atdot (x, y) of a dot corresponding to the imported image,

[0114] I_(i) represents the imported image made up of a set of dots,

[0115] P_(i)(x, y) represents geometric transforms, including rotation,scaling, distortion and may also include chromatic transforms ofimported dot x, y,

[0116] γ_(i)(x, y) is an additional position dependent term that canaffect the color value of pixel (x, y),

[0117] Each of the terms φ_(i)(x, y) I_(i)[Pi(x, y)] and γ_(i)(x, y) maybe nil, while the term α_(i)(x, y) φ_(i−1)(x, y) should generally neverbe nil for all the dots (x, y). There is generally no part in observingall of the prior image.

[0118] Due to the form of the elementary operations, they can becombined to yield a global function that has a simple structure. Theglobal function, defined below, defines the color value at point x, yfor an image composed of a number of layers:$\left( {{\sum\limits_{j = 1}^{j = q}\left\lbrack {{\alpha_{j}\left( {x,y} \right)} \cdot {I_{j}\left\lbrack {P_{j}\left( {x,y} \right)} \right\rbrack}} \right)} + {{\gamma \left( {x,y} \right)}\text{or~~alternatively}{\sum\limits_{j = 1}^{j = q}\left\lbrack {{{\alpha_{j}\left( {x,y} \right)} \cdot {I_{j}\left\lbrack {P_{j}\left( {x,y} \right)} \right\rbrack}} + {{\gamma \left( {x,y} \right)}\text{or~~alternatively}{\sum\limits_{j = 1}^{j = q}{{\alpha_{j}\left( {x,y} \right)} \cdot {I_{j}\left\lbrack {P_{j}\left( {x,y} \right)} \right\rbrack}}}} + {\gamma \left( {x,y} \right)}} \right.}}} \right.$

[0119] q=number of imported images that make a visible contribution atpoint x, y, in this global function:

[0120] α_(j)(x, y) is a scalar analogous to the scalar α_(i)(x, y) of aelementary function and α_(j)(x, y).neq. 0 (not equal to zero at atleast one point).

[0121] I_(j) represents an image or layer j to import

[0122] P_(j)(x, y) is P_(i) an import function analogous to the previousimport functions P_(i)(x, y)

[0123] γ(x, y) is a chromatic function analogous to chromatic functionsγ_(i)(x, y),

[0124] in this procedure, the global function can be generated, but notyet computed, for one point within each grid (depicted in FIG. 4).

[0125] since the grid represents a subset of the pixels required for theRIP, it is necessary to generate the remaining points, within each grid.For each additional point in the grid a new function is created byinterpolating the function between the two nearest points where theglobal function has been computed. This process is termed functionalinterpolation. The simplest form of the function is to created aweighted average based on distance.

[0126] As an example, assume the grids are 16×16 and the global functionhas been created for dots (1,1) and (1,17). Further, that the globalfunction at dot (1,1) yields cos(x, y) when simplified and the globalfunction at dot (17,1) yields sin(x, y) when simplified. Then theinterpolated function at point (1,8) will be (9/16)cos(x,y)+(7/16)sin(x, y). If the use of a 4×4 box is employed, and points 1and 5 computed, the computer is very fast. Point 3 is a simple add anddivide by 2 of points 1 and 5. Point 2 is the same average of points 1and 3. See FIG. 4A.

[0127] the functions that have been obtained for each pixel, some beingglobal functions and some being interpolated functions, are calculatedfor each pixel.

[0128] The subject method is particularly efficient for image processingfor two reasons: the global function has a relatively simple form andthus can be easily computed, and very little computation is required togenerate the interpolated functions. Use of functional interpolationprovides a major time saving. For example, when 4×4 grids of 16 pixelsare used the global function is generated only for {fraction (1/16)} ofthe total pixels. It is because of this that high speed, real-time,image processing can be achieved.

[0129] The changes to the image caused by the operator actions arecarried out and displayed almost instantaneously, i.e. in real time. Theoperator may, at any moment return and redo a elementary operation. Thisis because different actions and their results (i.e., the layers) aredefined by simple elementary equations. These can be easily modified.

[0130] In this way, the invention allows for any image effect, such asairbrushing, blurring, contrasting, dissolving effects, colormodifications, in short any operation concerning image graphics andcolor. The invention also enables geometrical transformations ormodifications, such as rotation, changes of scale, etc. Using FITS, amicrocomputer system can follow the actions of the operator, using inputmeans such as in general a mouse or light pen on an interactive tracingtable, in real time.

[0131] This input (e.g. pen) provides two types of command signals: oneis a position signal giving the coordinates (x, y) of the dot concerned,and if necessary its environment (for example the path of an airbrushstroke); the other uses the pressure of the pen on the table to create asecond type of signal. In the airbrush example, it would govern thedensity of the color being “sprayed”.

[0132] The parameters for each elementary operation are constantlyupdated as the work evolves. To save space and time, only the parametersfor dots in the definition grid that have a value or which are show avariation relative to their neighbors are stored. In this way theoperator can access, at any moment, either the present overall result ofall the operations, or intermediate results corresponding to one orseveral layers. Thus, the operator can intervene and modify a layerwithout affecting other layers. The link between the layers is only atthe level of recurrence and are taken into account during the RIP stage.

[0133] When all the necessary operations are finished, and the operatorwishes to produce the final image or an intermediate image at a givendefinition, the operator orders a raster image processing (RIP) at therequired image definition. The RIP computes only those pixels necessaryto update the screen, taking into account the portion of the image beingdisplayed and the zoom factor.

[0134] The number of dots for which the global function should begenerated during image editing within a layer are, in general,relatively small because function evolves with little variation (itssecond derivative is generally very low for most of the dots in theimage). Function only varies substantially at dots corresponding to alarge color change.

[0135] The grid chosen for the definition of elementary functions mayhave an equal mesh at all points. Alternatively, it may be constructedusing a different sized mesh at various points, depending on whether theimage zone covers an area of small or great variation to facilitateprocessing and correction.

[0136] Even if the final image is unsatisfactory, e.g. the control runhas been carried out and a proof image printed, it is still possible togo back and correct any intermediate stage to yield a better result.

[0137] An alternative method for processing image data in a computerizedsystem, which comprises:

[0138] (a) sampling an original image to be processed with a definitiongrid so as to retain a predetermined number of dots from all of the dotscontained within the original image, the predetermined number beingapproximately equal to the number that can be displayed on a monitorscreen to obtain a resulting image; and

[0139] (b) processing the resulting image into elementary recurrentoperations each broken down into three parts and providing, based on theresult of the previous elementary operation, these three parts added toeach other representing:

[0140] first, adopting color dot at position coordinates (x, y) in thenew layer (i) from previous layer (i−1) with a weighing (α_(i)) rangingfrom 0 to ±100%,

[0141] second, importing a color dot from external image (Ii) into thelayer i, after any desired chromatic and geometric transformation(P_(i)(x, y)) of this dot to add it to the color dot (x, y) of the layer(i), the degree of replacement of the dot of the layer (i) by the dotimported from the image (Ii) being defined by a scaler (β_(i)(x, y))with values from 0 to ±100%, and

[0142] third, chromatically modifying (γ_(i)(x, y)) on dot (x, y) oflayer (i),

[0143] each elementary operation (i) being defined by the equation

[0144] φ_(i)(x,y)=α_(i)(x,y)·φ_(i−1)(x,y)+β_(i)(x,y)·I _(i) [P_(i)(x,y)]+γ_(i)(x,y)

[0145] taking account of the previous operation (i−1),

[0146] wherein:

[0147] α_(i)(x, y) is a scaler function of the dot (x, y) correspondingto the presence at this dot of the image resulting from the previouselementary operation φ_(i−1)(x, y),

[0148] φ_(i−1)(x, y) is a function representing the previous elementaryoperation,

[0149] β_(i)(x, y) is scaler function corresponding to the presence atdot (x, y) of a dot corresponding to the imported image,

[0150] I_(i) represents the imported image made up of a set of dots,

[0151] P_(i)(x, y) is the function of image import representing thechromatic geometric transfer of one of the set of dots in the imagetowards the layer (i), to which is applied the elementary operationφ_(i)(x, y),

[0152] I_(i)[P_(i)(x, y)] is the function corresponding to the import ofthe image,

[0153] γ_(i)(x, y) is a chromatic function representing a colortransformation function carried out on a dot (x, y),

[0154] each of the terms β_(i)I_(i)pP_(i)(x, y)] and γ_(i)(x, y) can bezero while the term α_(i)(x, y) φ_(i−1)(x, y) is normally never zero forall the dots (x, y);

[0155] the elementary operations are effected to obtain a functionrepresenting i first elementary operations to obtain a function whoseparameters are defined at all the dots of the definition grid${\sum\limits_{j = 1}^{j = q}{\alpha_{j}{\left( {x,y} \right) \cdot {I_{j}\left\lbrack {P_{j}\left( {x,y} \right)} \right\rbrack}}}} + {\gamma \left( {x,y} \right)}$

[0156]  wherein,

[0157] q=number of imported images,

[0158] α_(j)(x, y) is a scaler analogous to the scaler α_(i)(x, y) of aelementary function,

[0159] I_(j) represents an image j to import,

[0160] P_(j)(x, y) is an import function analogous to the previousimport functions P_(i)(x, y),

[0161] γ(x, y) is a chromatic function analogous to chromatic functionsγ_(i)(x, y),

[0162] the global function being defined by interpolating it at theintermediate dots between the dots of the definition grid, theseintermediate dots depending on the definition required for the finalimage, the pixels being calculated for each dot to be obtained.

[0163] A system for using this method generally comprises: (a) means forsampling an original image to be processed with a definition grid so asto retain a predetermined number of dots from all of the dots containedwithin the original image, the predetermined number being approximatelyequal to the number that can be displayed on a monitor screen to obtaina resulting image, and (b) means for processing the resulting image intoelementary recurrent operations each broken down into three parts andproviding, based on the result of the previous elementary operation,these three parts added to each other representing the old image, a newimported image and a color change, as above.

[0164] The elementary operations are effected to obtain a functionrepresenting i first elementary operations to obtain a function whoseparameters are defined at all the dots of the definition grid, using thesummation function above.

[0165] The global function is defined by interpolating it at theintermediate dots between the dots of the definition grid, theseintermediate dots depending on the definition required for the finalimage, the pixels being calculated for each dot to be obtained.

EXAMPLES

[0166] 1) Airbrushing:

[0167] This involves in making a line with a color. As this lineimitates that made by an airbrush, it can be treated as a succession ofcolored dots created by the airbrush spray. The distribution of thecolor density in a airbrush dot is a Gaussian function. This means thatthe intensity of the color is at its greatest in the center of the dot,diminishing towards the edges as a Gauss function. In a real airbrush,the intensity depends on the pressure exerted on the trigger, whichwidens or otherwise changes the ink spray within the air jet. Such apressure can be simulated in a computerized system by representing (asexplained above) a dot by a circle of color with a density variationbetween the center and edge expressed as a Gauss function. Thesaturation at the center can vary between 0 and 1 (or zero and 100%).

[0168] To sum up, the line of an aerograph is a succession of coloreddisks, of which it is possible to modify the path (the location of thedisk centers), and the color density.

[0169] Based on the general equation (1) and the airbrushcharacteristics,

[0170] this equation becomes the following:$\quad\left\lbrack \begin{matrix}{{\phi_{i}\left( {x,y} \right)} = {{{\alpha_{i}\left( {x,y} \right)}{\phi_{i - 1}\left( {x,y} \right)}} + {\gamma_{i}\left( {x,y} \right)}}} \\{{\beta_{i}\left( {x,y} \right)} = {0{\forall\left( {x,y} \right)}}} \\{{\gamma_{i}\left( {x,y} \right)} = {\left\lbrack {1 - {\alpha_{i}\left( {x,y} \right)}} \right\rbrack \cdot C}} \\{C = {{color}\quad {constant}\quad {of}\quad {the}\quad {``{{projected}\quad {material}}"}}}\end{matrix} \right.$

[0171] and the general equation becomes the following:

φ_(i)(x,y)=α_(i)(x,y)φ_(i−1)(x,y) +[1−α_(i)(x,y)]·C

[0172] As there is no imported image in the path of the airbrush, thecoefficient of presence β_(i) of an external image is nil at all pointsof the layer.

[0173] The application of the airbrush consists in replacing partiallyor totally the previous shade of a dot by the shade of the color“projected” by the airspray. Because of this, the chromatic functionγ_(i)(x, y) is expressed as a function of the color C and as acomplement 1 to the coefficient of presence of the previous image, thatis

[0174] The choice of scaler α_(i)(x, y) at each dot translates thedensity of color left by the airbrush.

[0175] The function of color presence α_(i)(x, y) or [1−α_(i)(x, y)],i.e. {overscore (α)}_(i), can be represented by a Gauss functioncentered on one dot, limited for example to 10% at the edge of the disk.In other words, the two extreme ends of the Gaussian curve beyond 10%(or any other value which may be selected) are suppressed. This meansthat the Gauss function will not be applied beyond the disk radiuschosen.

[0176] 2) Image fusion:

[0177] This operation imports an external image into an existing one.Based on the general equation, this importation operation is defined asfollows:

[0178] In the general equation (1) to which are applied the particularconditions relating to this operation: $\quad\left\lbrack \begin{matrix}{{\phi_{i}\left( {x,y} \right)} = {{{\alpha_{i}\left( {x,y} \right)}{\phi_{i - 1}\left( {x,y} \right)}} + {{\beta_{i}\left( {x,y} \right)}I_{i}{P_{i}\left( {x,y} \right)}}}} \\{{\gamma_{i}\left( {x,y} \right)} = 0} \\{{\beta_{i}\left( {x,y} \right)} = {\left\lbrack {1 - {\alpha_{i}\left( {x,y} \right)}} \right\rbrack = {\overset{\_}{\alpha}}_{i}}}\end{matrix} \right.$

[0179] The chromatic function γ_(i) is zero and the coefficients α_(i)and β_(i) are complementary coefficients (their sum is equal to one).

[0180] In fact, as a hypothesis for this type of operation, a dot of theimported image replaces, more or less, or even completely, a dot of theprevious image. This corresponds in the first instance to a more or lesspronounced dissolve and in the second to the replacement of the part ofthe previous image within the contour of the imported one.

[0181] The equation below can be simplified and thus gives the equationfor image fusion:

φ_(i)(x,y)=α_(i)(x,y)φ_(i−1)(x,y) +{overscore (α)}_(i)(x,y)I _(i) P_(i)(x,y)

[0182] 3) Lightening/darkening

[0183] It should be noted that in the general equation of a layer i, thescaler α_(i) should never be zero at all points of the layer. On theother hand, if there is no image importation, the scaler β_(i) should bezero at every point (x, y).

[0184] To lighten or darken an image, it is necessary to use thechromatic function γ_(i)(x, y). As explained above, the general functionφ_(i)(x, y) should not be limited to only the chromatic function, forthis would mean suppressing all the images in layers 1 to i−1(disappearance of φ_(i−1)), that is, the recurrence.

[0185] The darken/lighten function therefore assists in adding a colorto the color at the previous dot x, y (function of φ_(i−1)).

[0186] Based on the general equation, as follows:

φ_(i)(x,y)=α_(i)(x,y)·φ_(i−1)(x,y) +β_(i)(x,y)I _(i)(P_(i)(x,y))+γ_(i)(x,y)

[0187] in which: $\quad\left\lbrack \begin{matrix}{{\alpha_{i}\left( {x,y} \right)} = {1{\forall\left( {x,y} \right)}}} \\{{\beta_{i}\left( {x,y} \right)} = {0{\forall\left( {x,y} \right)}}}\end{matrix} \right.$

[0188] We obtain:

φ_(i)(x,y)=φ_(i−1)(x,y)+γ_(i)(x,y)

[0189] 4) Deformationl anamorphosis:

[0190] This operation can be applied to an existing or image. In fact,if it is desired to transform part of the image of the layer (i−1), thispart of the image is considered as an imported image to be treated asdescribed below.

[0191] The deformation/anamorphosis of an image consists of linking toeach node a vector of deformation with a direction and sizecorresponding to the desired deformation. It deformation is uniform overall the relevant part of the image, each node will have attached to itvectors of the same size and direction, which will move the dotcorresponding to each node as defined by each vector. The same samplingfor the RIP can be used to limit the vector calculation for a group. ofpixels (e.g. 4×4) by computing only the origin and points just outsidethe 4×4 grid, and the functionally interpolating, thus speedingcomputation time.

[0192] To achieve such a deformation, the general function of the layeri becomes as follows through the use of the equation defining imageimport:

φ_(i)(x,y)=α_(i)(x,y)φ_(i−1)(x,y) +{overscore (α)}_(i)(x,y)I _(i) P_(i)(x,y)

[0193] The deformation or anamorphosis consists in working on the importfunction P_(i)(x, y).

[0194] 5) Levelling:

[0195] Levelling a color in part of an image, as an example, in aportrait, enables the operator to remove local skin defects, such asbirthmarks. To achieve this, the average intensity of the color iscalculated in a disk centered on each node of the part of the image tobe processed. Depending on the radius selected, the color will be mademore or less uniform. This operation combines the normal image withanother which has been averaged out.

[0196] 6) Contrasting:

[0197] Opposite to the previous type of processing, contrasting involvesaccentuating the fineness of the lines in a drawing or photograph. in aportrait, for example, it would bring out individual hairs of ahairstyle. This would also be useful for surveillance photography.

[0198] To achieve this, it is necessary to increase the high-frequencywavelength harmonics without touching the low frequency ones (near theaverage). The local average would be substituted from individual pixels,accentuating all changes, in the opposite manner from leveling.

[0199] The subject invention has been described in terms of itspreferred embodiments. Upon reading the disclosure, various alternativeswill become obvious to those skilled in the art. These variations are tobe considered within the scope and spirit of the subject invention,which is only to be limited by the claims which follow and theirequivalents.

What is claimed is:
 1. A method of image processing in a computerizedsystem, which comprises: (a) supplying data defining an original imageinto the system; (b) assigning pixels from the original image to pixelsin a new first image format so that the first image is organized intogroups of pixels, each of the groups being individually compressible toyield a reduced size image; and (c) reducing the number of assignedpixels to form a reduced resolution image by averaging a particularnumber of adjacent pixels falling within a first predetermined area intoa first averaged pixel, organized by the groups of pixels, andperforming this computation across the entire first image format, toform a reduced definition image.
 2. A method of claim 1 furthercomprising reducing the number of the first averaged pixels by averaginggroups of pixels falling within a second predetermined area into asecond averaged pixel, organized by the groups of pixels, performingthis computation across the entire second image format, and repeatingthis step until a preselected or lower number of pixels remain, theremaining pixels forming a reduced definition image.
 3. A method ofclaim 1 further comprising modifying the data defining the reduceddefinition image to obtain a desired result and saving a copy of thedata defining the pixels forming the desired result.
 4. A method ofclaim 3 further comprising adding the data defining the original imageto the data defining the pixels forming the desired result, and formingan image from the added data.
 5. A method of claim 1, wherein thereducing the number of pixels in step (c) comprises averaging fourpixels in a 2×2 matrix to produce a single averaged pixel.
 6. A methodof raster image processing, which comprises: (a) adding data defining anoriginal image to data defining modifications to a reduced definitionimage; and (b) forming an image from the added data.
 7. A method forprocessing image data in a computerized system, which comprises: (a)sampling an original image to be processed with a definition grid so asto retain a predetermined number of dots from all of the dots containedwithin the original image, the predetermined number being approximatelyequal to the number that can be displayed on a monitor screen to obtaina resulting image; and (b) processing the resulting image intoelementary recurrent operations each broken down into three parts andproviding, based on the result of the previous elementary operation,these three parts added to each other representing: first, adoptingcolor dot at position coordinates (x, y) in the new layer (i) fromprevious layer (i−1) with a weighing (α_(i)) ranging from 0 to ±100%,second, importing a color dot from external image (I_(i)) into the layeri, after any desired chromatic and geometric transformation (P_(i)(x,y)) of this dot to add it to the color dot (x, y) of the layer (i), thedegree of replacement of the dot of the layer (i) by the dot importedfrom the image (I_(i)) being defined by a scaler (β_(i)(x, y)) withvalues from 0 to ±100%, and third, chromatically modifying (γ_(i)(x, y))on dot (x, y) of layer (i), each elementary operation (i) being definedby the equation φ_(i)(x,y)=α_(i)(x,y)·φ_(i−1)(x,y)+β_(i)(x,y)·I _(i) [P_(i)(x,y)]+γ_(i)(x,y) taking account of the previous operation (i−1),wherein: α₁(x, y) is a scaler function of the dot (x, y) correspondingto the presence at this dot of the image resulting from the previouselementary operation φ_(i−1)(x, y), φ_(i−1)(x, y) is a functionrepresenting the previous elementary operation, β_(i)(x, y) is scalerfunction corresponding to the presence at dot (x, y) of a dotcorresponding to the imported image, I_(i) represents the imported imagemade up of a set of dots, P_(i)(x, y) is the function of image importrepresenting the chromatic or geometric transformation, or both, of oneof the set of dots in the image towards the layer (i), to which isapplied the elementary operation φ_(i)(x, y), I_(i)[P_(i)(x, y)] is thefunction corresponding to the import of the image, γ_(i)(x, y) is achromatic function representing a color transformation function carriedout on a dot (x, y), each of the terms β_(i)I_(i)[P_(i)(x, y)] andγ_(i)(x, y) can be zero while the term α_(i)(x, y) φ_(i−1)(x, y) isnever zero for all the dots (x, y); the elementary operations areeffected to obtain a function representing i first elementary operationsto obtain a function whose parameters are defined at all the dots of thedefinition grid${\sum\limits_{j = 1}^{j = q}{\alpha_{j}{\left( {x,y} \right) \cdot {I_{j}\left\lbrack {P_{j}\left( {x,y} \right)} \right\rbrack}}}} + {\gamma \left( {x,y} \right)}$

 wherein, q=number of imported images, α_(j)(x, y) is a scaler analogousto the scaler α_(i)(x, y) of a elementary function, I_(j) represents animage j to import, P_(j)(x, y) is an import function analogous to theprevious import functions Pi(x, y), γ(x, y) is a chromatic functionanalogous to chromatic functions γ_(i)(x, y), the global function beingdefined by interpolating it at the intermediate dots between the dots ofthe definition grid, these intermediate dots depending on the definitionrequired for the final image, the pixels being calculated for each dotto be obtained.
 8. A computerized system for image processing, whichcomprises: (a) means for assigning pixels from an original image topixels in a new first image format so that the first image is organizedinto compressible groups of pixels; and (b) means for reducing thenumber of assigned pixels to form a reduced resolution image byaveraging a particular number of adjacent pixels falling within a firstpredetermined area into a first averaged pixel, organized across theentire first image format, to form a reduced definition image.
 9. Acomputerized system of claim 8 further, comprising means for reducingthe number of the first averaged pixels by averaging groups of pixelsfalling within a second predetermined area into a second weightedaveraged pixel, organized by the groups of pixels, performing thiscomputation across the entire image format, and repeating this stepuntil a preselected number of pixels remain, the remaining pixelsforming a reduced definition image.
 10. A computerized system for rasterimage processing, which comprises: (a) means for adding data definingpixels forming an original image to data defining modifications to areduced definition image; and (b) means for forming an image from theadded data.
 11. A computerized system for processing image data whichcomprises: (a) means for sampling an original image to be processed witha definition grid so as to retain a predetermined number of dots fromall of the dots contained within the original image, the predeterminednumber being approximately equal to the number that can be displayed ona monitor screen to obtain a resulting image; and (b) means forprocessing the resulting image into elementary recurrent operations eachbroken down into three parts and providing, based on the result of theprevious elementary operation, these three parts added to each otherrepresenting: first, adopting color dot (x, y) in the new layer (i) fromprevious layer (i−1) with a weighing (α_(i)) ranging from 0 to ±100%,second, importing a color dot from external image (I_(i)) into the layeri, after chromatic or geometric transformation, or both, (P_(i)(x, y))of this dot to add it to the color dot (x, y) of the layer (i), thedegree of replacement of the dot of the layer (i) by the dot importedfrom the image (Ii) being defined by a scaler (β₁(x, y)) with valuesfrom 0 to ±100%, third, chromatically modifying (γ_(i)(x, y)) on dot (x,y) of layer (i), each elementary operation (i) being defined by theequation φ_(i)(x,y)=α_(i)(x,y)·φ_(i−1)(x,y)+β_(i)(x,y)·I _(i) [P_(i)(x,y)]+γ_(i)(x,y) taking account of the previous operation (i−1),wherein: α_(i)(x, y) is a scaler function of the dot (x, y)corresponding to the presence at this dot of the image resulting fromthe previous elementary operation φ¹⁻¹(x, y), φ¹⁻¹(x, y) is a functionrepresenting the previous elementary operation, β_(i)(x, y) is scalerfunction corresponding to the presence at dot (x, y) of a dotcorresponding to the imported image, I_(i) represents the imported imagemade up of a set of dots, P_(i)(x, y) is the function of image importrepresenting the chromatic geometric transfer of one of the set of dotsin the image towards the layer (i), to which is applied the elementaryoperation φ₁(x, y), I_(i)[P_(i)(x, y)] is the function corresponding tothe import of the image, γ_(i)(x, y) is a chromatic functionrepresenting a color transformation function carried out on a dot (x,y), each of the terms β_(i)I_(i)[P_(i)(x, y)] and γ_(i)(x, y) can bezero while the term α_(i)(x, y)·φ_(i−1)(x, y) is never zero for all thedots (x, y); the elementary operations are effected to obtain a functionrepresenting i first elementary operations to obtain a function whoseparameters are defined at all the dots of the definition grid${\sum\limits_{j = 1}^{j = q}{\alpha_{j}{\left( {x,y} \right) \cdot {I_{j}\left\lbrack {P_{j}\left( {x,y} \right)} \right\rbrack}}}} + {\gamma \left( {x,y} \right)}$

 wherein, q=number of imported images, α_(j)(x, y) is a scaler analogousto the scaler α_(i)(x, y) of a elementary function, I_(j) represents animage j to import, P_(j)(x, y) is an import function analogous to theprevious import functions Pi(x, y), γ(x, y) is a chromatic functionanalogous to chromatic functions γi(x, y), the global function beingdefined by interpolating it at the intermediate dots between the dots ofthe definition grid, these intermediate dots depending on the definitionrequired for the final image, the pixels being calculated for each dotto be obtained.